Simulating secondary organic aerosol in a regional air quality model ; using the statistical oxidation model – Part 3: Assessing the influence of ; semi-volatile and intermediate volatility organic compounds and NO<sub>X</sub> Journal Article uri icon

Overview

abstract

  • Abstract. Semi-volatile and intermediate-volatility organic compounds (SVOCs and IVOCs) from anthropogenic sources are likely to be important precursors of secondary organic aerosol (SOA) in urban airsheds yet their treatment in most models is based on limited and obsolete data, or completely missing. Additionally, gas-phase oxidation of organic precursors to form SOA is influenced by the presence of nitric oxide (NO), but this influence is poorly constrained in chemical transport models. In this work, we updated the organic aerosol model in the UCD/CIT chemical transport model to include (i) a semi-volatile and reactive treatment of primary organic aerosol (POA), (ii) emissions and SOA formation from IVOCs, (iii) the NOX influence on SOA formation, and (iv) SOA parameterizations for SVOCs and IVOCs that are corrected for vapor wall loss artifacts during chamber experiments. All updates were implemented in the statistical oxidation model (SOM) that simulates the chemistry, thermodynamic properties, and gas/particle partitioning of organic aerosol (OA). Model treatment of POA, SVOCs, and IVOCs was based on an interpretation of a comprehensive set of source measurements and resolved broadly by source type. The NOX influence on SOA formation was calculated offline based on measured and modeled VOC:NOX ratios. And finally, the SOA formation from all organic precursors (including SVOCs and IVOCs) was modeled based on recently derived parameterizations that accounted for vapor wall loss artifacts in chamber experiments. The updated model was used to simulate a two week summer episode over southern California at a model resolution of 8 km. When combustion-related POA was treated as semi-volatile, modeled POA mass concentrations were reduced by 30–50 % in the urban areas in southern California but were still too high when compared against measurements made at Riverside, CA during the Study of Organic Aerosols at Riverside (SOAR-1) campaign of 2005. Treating all POA (except that from marine sources) to be semi-volatile resulted in a larger reduction in POA mass concentrations and allowed for a better model-measurement comparison at Riverside. Model predictions suggested that both SVOCs (evaporated POA vapors) and IVOCs did not contribute significantly to SOA mass concentrations in the urban areas (<5 % and <15 % of the total SOA respectively) as the timescales for SOA production appeared to be shorter than the timescales for transport out of the urban airshed. Comparisons of modeled IVOC concentrations with measurements of anthropogenic SOA precursors in southern California seemed to imply that IVOC emissions were underpredicted in our updated model by a factor of 2. We suspect that these missing IVOCs might arise from the use of volatile chemical products such as pesticides, coatings, cleaning agents, and personal care products. Correcting for the vapor wall loss artifact in chamber experiments enhanced SOA mass concentrations although the enhancement was precursor- as well as NOX-dependent. Accounting for the influence of NOX using the VOC:NOX ratios resulted in better predictions of OA mass concentrations in rural/remote environments but still underpredicted OA mass concentrations in urban environments, potentially due to the missing urban emissions/chemical source of OA. Finally, simulations performed for the year 2035 showed that despite reductions in VOC and NOX emissions in the future, SOA mass concentrations may be higher than in the year 2005, primarily from increased hydroxyl radical (OH) concentrations due to lower ambient NO2 concentrations.;

publication date

  • July 10, 2018

has restriction

  • green

Date in CU Experts

  • November 13, 2020 4:26 AM

Full Author List

  • Akherati A; Cappa CD; Kleeman MJ; Docherty KS; Jimenez JL; Griffith SM; Dusanter S; Stevens PS; Jathar SH

author count

  • 9

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